1. Field of the Invention
The present invention relates to an image processing device and an image processing method which are suitable for a process of a cone-beam CT (computerized tomography) image.
2. Related Background Art
FIG. 2 shows the outline of a cone-beam X-ray CT device (or scanner).
In FIG. 2, X-rays irradiated from an X-ray tube 103 are absorbed and attenuated inside the body of a subject 102, and the X-rays that have passed through the subject 102 are detected on a surface sensor 101. Then, the X-ray tube 103 and the surface sensor 101 are rotated around the subject 102 without changing the relative physical relationship between the X-ray tube 103 and the surface sensor 101, whereby the projection image data of the subject 102 for a full one rotation is acquired. Thus, the projection image data acquired like this is subjected to a reconstruction process, whereby the tomographic image of the subject 102 is acquired. Incidentally, to acquire the same tomographic image, the subject 102 may be rotated instead of rotating the X-ray tube 103 and the surface sensor 101.
In the reconstruction process, a convolution process is first executed on the projection image data as shown in FIG. 3, and the convolution-processed projection image data is then subjected to back projection to each pixel of the reconstruction image as shown in FIG. 4.
To execute the reconstruction process at high speed, for example, a multiprocessor is used. Here, it should be noted that the method of achieving the high-speed reconstruction process by using the multiprocessor is described in “Reconstruction of 3-D X-ray Computerized Tomography Images Using a Distributed Memory Multiprocessor System”, Tohru Sasaki and Yasushi Fukuda, Information Processing Society of Japan Transaction, Vol. 38, No. 9 (hereinafter called “document 1”). In this method, the parallel processes are achieved by using plural processors, and also the data is transferred at high speed. That is, the high-speed reconstruction process is achieved mainly by means of hardware.
However, the following important problems occur in the cone-beam CT. In the conventional technique, the projection image data acquired all over the projection angles is line data corresponding to the one-dimensional fan beam. However, in the cone-beam CT, the projection image data is two-dimensional image data, and as a result the amount of data necessary in the process is huge. For this reason, if the convolution process is executed on that huge amount of data as in the method described in document 1, it is inefficient, and thus, it is impossible to achieve the high-speed reconstruction process by the hardware. Moreover, even if the parallel processes are executed, a huge amount of projection image data must be stored in the local memory of each of the processing units, whereby the capacity of each local memory must be made very large, at a high cost.